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Multi-objective maximum diversity problem
2017 XLIII Latin American Computer Conference (CLEI), 2017The Maximum Diversity (MD) problem is the process of selecting a subset of elements where the diversity among selected elements is maximized. Several diversity measures were already studied in the literature, optimizing the problem considered in a pure mono-objective approach.
Katherine Vera +3 more
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Multi-objective Phylogenetic Algorithm: Solving Multi-objective Decomposable Deceptive Problems
2011In general, Multi-objective Evolutionary Algorithms do not guarantee find solutions in the Pareto-optimal set. We propose a new approach for solving decomposable deceptive multi-objective problems that can find all solutions of the Pareto-optimal set.
Jean Paulo Martins +3 more
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Multi-objective Nurse Rerostering Problem
2016How to schedule a limited number of nurses in hospital wards staffed 24 h a day is important issue for the satisfactory patient care and potentially improve nurse retention. Nurse Scheduling Problem (NSP) is a combinatorial optimization problem, in which a set of nurses must be assigned into a limited set of working slots, subject to a given set of ...
Shih-Min Wu +3 more
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Approximating Multi-objective Knapsack Problems
2001For multi-objective optimization problems, it is meaningful to compute a set of solutions covering all possible trade-offs between the different objectives. The multi-objective knapsack problem is a generalization of the classical knapsack problem in which each item has several profit values.
Thomas Erlebach +2 more
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Reliability Models for Multi-Objective Design Problems
2020Nowadays, shared network infrastructures are being designed for supporting various services that may be subject to diverse failures and disruptions due to the malfunctioning of network component(s) or human-caused disasters. As the delivery of these services may be subject to multiple correlated failures and disruptions, the present chapter develops a ...
Papadimitriou, Dimitri +2 more
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A MULTI-OBJECTIVE ROUTING PROBLEM
Engineering Optimization, 1986A dynamic programming formulation is proposed for finding all Pareto optimal solutions for a routing problem within a specified overall cost, overall time and overall distance. A method is also proposed for finding other solutions which are not Pareto optimal solutions but which lie within the specified overall cost, overall time and overall distance.
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2000
Many of the problems in the world of software re-engineering are reasonably conducive to the use of evolutionary methods. There is often only vague or even inaccurate information available on how one should approach particular problems. To further complicate matters, there are often several — possibly even conflicting — criteria by which the product is
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Many of the problems in the world of software re-engineering are reasonably conducive to the use of evolutionary methods. There is often only vague or even inaccurate information available on how one should approach particular problems. To further complicate matters, there are often several — possibly even conflicting — criteria by which the product is
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Multi‐objective combinatorial optimization problems: A survey
Journal of Multi-Criteria Decision Analysis, 1994AbstractIn the last 20 years many multi‐objective linear programming (MOLP) methods with continuous variables have been developed. However, in many real‐world applications discrete variables must be introduced. It is well known that MOLP problems with discrete variables can have special difficulties and so cannot be solved by simply combining discrete ...
Ulungu, E. L., Teghem, J.
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A multi-objective Artificial Bee Colony for optimizing multi-objective problems
2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 2010This work proposes a multi-objective artificial bee colony (MOABC) for optimizing problems with multiple objectives. We have adapted the original Artificial Bee Colony (ABC) algorithm to multi objective problems with a grid-based approach for maintaining and adaptively assessing the Pareto front.
Ramin Hedayatzadeh +3 more
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An improved multi-objective particle swarm optimizer for multi-objective problems
Expert Systems with Applications, 2010This paper proposes an improved multi-objective particle swarm optimizer with proportional distribution and jump improved operation, named PDJI-MOPSO, for dealing with multi-objective problems. PDJI-MOPSO maintains diversity of new found non-dominated solutions via proportional distribution, and combines advantages of wide-ranged exploration and ...
Shang-Jeng Tsai +5 more
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